Hi List,
This is to announce the release of PyTables 2.2 final.
I've finally declared Blosc stable and I'm very happy to say that Blosc is
showing very good results on every benchmark that I'm doing with PyTables.
I'd like to thank all of those that have collaborated on its intensive
testing.
Well, I hope you will like the new release too!
Francesc
=
Announcing PyTables 2.2 (final)
=
I'm happy to announce PyTables 2.2 (final). After 18 months of
continuous development and testing, this is, by far, the most powerful
and well-tested release ever.
What's new
==
The main new features in 2.2 series are:
* A new compressor called Blosc, designed to read/write data to/from
memory at speeds that can be faster than a system `memcpy()` call.
With it, many internal PyTables operations that are currently
bounded by CPU or I/O bandwith are speed-up. Some benchmarks:
http://blosc.pytables.org/trac/wiki/SyntheticBenchmarks
And a demonstration on how Blosc can improve PyTables performance:
http://www.pytables.org/docs/manual/ch05.html#chunksizeFineTune
* Support for HDF5 hard links, soft links and external links (kind of
mounting external filesystems). A new tutorial about its usage has
been added to the 'Tutorials' chapter of User's Manual. See:
http://www.pytables.org/docs/manual/ch03.html#LinksTutorial
* A new `tables.Expr` module (based on Numexpr) that allows to do
persistent, on-disk computations on many algebraic operations.
For a brief look on its performance, see:
http://pytables.org/moin/ComputingKernel
* Suport for 'fancy' indexing (i.e., à la NumPy) in all the data
containers in PyTables. Backported from the implementation in the
h5py project. Thanks to Andrew Collette for his fine work on this!
* Binaries for both Windows 32-bit and 64-bit are provided now.
As always, a large amount of bugs have been addressed and squashed too.
In case you want to know more in detail what has changed in this
version, have a look at:
http://www.pytables.org/moin/ReleaseNotes/Release_2.2
You can download a source package with generated PDF and HTML docs, as
well as binaries for Windows, from:
http://www.pytables.org/download/preliminary
For an on-line version of the manual, visit:
http://www.pytables.org/docs/manual-2.2
What it is?
===
PyTables is a library for managing hierarchical datasets and designed to
efficiently cope with extremely large amounts of data with support for
full 64-bit file addressing. PyTables runs on top of the HDF5 library
and NumPy package for achieving maximum throughput and convenient use.
Resources
=
About PyTables:
http://www.pytables.org
About the HDF5 library:
http://hdfgroup.org/HDF5/
About NumPy:
http://numpy.scipy.org/
Acknowledgments
===
Thanks to many users who provided feature improvements, patches, bug
reports, support and suggestions. See the ``THANKS`` file in the
distribution package for a (incomplete) list of contributors. Most
specially, a lot of kudos go to the HDF5 and NumPy (and numarray!)
makers. Without them, PyTables simply would not exist.
Share your experience
=
Let us know of any bugs, suggestions, gripes, kudos, etc. you may
have.
**Enjoy data!**
-- The PyTables Team
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